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An Optimal Energy Flow Calculation Method for Integrated Electricity-Gas System Applying Parametric Linear Programming
CAI Jie, ZHAO Haipeng, GUAN Qinyue, GUO Ting, ZHANG Di, MIAO Shihong
Electric Power Construction ›› 2022, Vol. 43 ›› Issue (1) : 29-37.
PDF(2868 KB)
PDF(2868 KB)
An Optimal Energy Flow Calculation Method for Integrated Electricity-Gas System Applying Parametric Linear Programming
The calculation of the optimal energy flow (OEF) of the integrated electricity-gas system (IEGS) is the basis of the optimal planning and operation analysis of IEGS. There are some problems in the existing methods for solving the OEF of the IEGS, such as frequent data interaction, poor convergence and difficulty in ensuring privacy. Therefore, a method for calculating the OEF applying parameter linear programming is proposed in this paper. Firstly, the optimal power flow (OPF) models for the power network and natural gas network are constructed, respectively. The OPF model of the power network adopts the optimal DC power flow model considering the active power loss. The OPF model of the natural gas network is established on the basis of the second-order cone relaxation. Secondly, the correlation function between the electricity-gas coupling power and the optimal solution of the power flow is constructed based on the parameter linear programming theory. Then, the correlation function is transferred to the natural gas system for joint optimization, and returns the electricity-gas coupling power information to the power system for solution. Thus, the natural gas flow and power flow results of the OEF are obtained. Through the simulation analysis, the method proposed in this paper can accurately solve the OEF through one-time information exchange. At the same time, the amount of interactive information is small and able to protect private information. It is suitable for the decomposition calculation of the OEF.
integrated electricity-gas system (IEGS) / optimal energy flow (OEF) / stochastic robust optimization / decomposition / privacy
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